Sayat Ibrayev¹, Batyrkhan Omarov^1,2,3,*, Arman Ibrayeva¹, Zeinel Momynkulov^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 229-249, 2024, DOI:10.32604/cmc.2024.053075 - 15 October 2024

Abstract This research paper presents a comprehensive investigation into the effectiveness of the DeepSurNet-NSGA II (Deep Surrogate Model-Assisted Non-dominated Sorting Genetic Algorithm II) for solving complex multi-objective optimization problems, with a particular focus on robotic leg-linkage design. The study introduces an innovative approach that integrates deep learning-based surrogate models with the robust Non-dominated Sorting Genetic Algorithm II, aiming to enhance the efficiency and precision of the optimization process. Through a series of empirical experiments and algorithmic analyses, the paper demonstrates a high degree of correlation between solutions generated by the DeepSurNet-NSGA II and those obtained from… More >

Wei Ji¹, Yingchun Bai^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011338

Abstract The superior stiffness-to-weight and strength-to-weight mechanical advantages of shell-infill structures can be fully exploited through concurrent design of the entire topology and infill configuration. This inherent design freedom can be guaranteed by additive manufacturing, through which complicated geometry can be fabricated. The existing approaches are typically focused on topology optimization with porous infill [1-3], un-prescribed lattice configuration with uniform density [4-8], or prescribed single lattice configuration with non-uniform density [9-10]. Towards higher performance yet lightweight, this work proposes a concurrent topology optimization approach to directly generate shell-infill structures in which the inner infill consists of… More >

Jie Zhang¹, Xu Zhou¹, Sanqiang Yang¹, Moubin Liu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-2, 2024, DOI:10.32604/icces.2024.012192

Abstract The lattice architecture, characterized by its methodical arrangement of repetitive units, exhibits compactness, uniformity, and lightweight properties. In additive manufacturing, such structures are widely utilized in support structures and internal fillings, playing a significant role in improving manufacturing efficiency and optimizing structural performance [1,2]. However, due to the complex microstructure of lattice materials, it is challenging to describe them using refined finite element models. The development of an equivalent performance model for these materials, employing a periodic single cell to represent the internal architecture for the comprehensive lattice system, can significantly improve computational efficiency and… More >

Hao Xu¹, Jing Wang², Rubin Zhu², Alfred Strauss³, Maosen Cao⁴, Zhanjun Wu^1,*

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 785-803, 2024, DOI:10.32604/sdhm.2024.051393 - 20 September 2024

Abstract Delamination is a prevalent type of damage in composite laminate structures. Its accumulation degrades structural performance and threatens the safety and integrity of aircraft. This study presents a method for the quantitative identification of delamination identification in composite materials, leveraging distributed optical fiber sensors and a model updating approach. Initially, a numerical analysis is performed to establish a parameterized finite element model of the composite plate. Then, this model subsequently generates a database of strain responses corresponding to damage of varying sizes and locations. The radial basis function neural network surrogate model is then constructed More >

Shuai Li¹, Xiaodong Zhao^1,2,*, Jinghu Zhou¹, Xiyue Wang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2587-2611, 2024, DOI:10.32604/cmes.2024.052203 - 08 July 2024

Abstract Accurate quantification of the uncertainty in the mechanical characteristics of dielectric solids is crucial for advancing their application in high-precision technological domains, necessitating the development of robust computational methods. This paper introduces a Conditional Generation Adversarial Network Isogeometric Analysis (CGAN-IGA) to assess the uncertainty of dielectric solids’ mechanical characteristics. IGA is utilized for the precise computation of electric potentials in dielectric, piezoelectric, and flexoelectric materials, leveraging its advantage of integrating seamlessly with Computer-Aided Design (CAD) models to maintain exact geometrical fidelity. The CGAN method is highly efficient in generating models for piezoelectric and flexoelectric materials, More >

Wei Zhang^1,2, Y. Lu¹, Liye Lv^1,3, Y. Mei³, Baochang Zhu³

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.39, No.4, pp. 1-8, 2023, DOI:10.23967/j.rimni.2023.10.005 - 27 October 2023

Abstract As an important part of the lifting platform of pallet forklift trucks, how to reduce the deformation of the pallet rack under working conditions while reducing the mass to ensure the safety performance of forklift trucks is the most concerning issue in the design of forklift truck structure. The pallet rack structure is complex, and optimizing simulation using traditional high-precision simulation models takes much time and effort. Therefore, this paper takes the lifting platform of an unmanned AVG forklift truck as the research object and establishes a parametric model of the pallet rack using the… More >

Liye Lv^1,22, Baochang Zhu¹, Y. Lu², Y. Mei¹, Yuan Song²

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.39, No.4, pp. 1-8, 2023, DOI:10.23967/j.rimni.2023.09.003 - 03 October 2023

Abstract Forklift is a kind of material handling robot, which is widely used in short-distance handling in the industrial field. However, at present, the structural design of forklifts is generally based on designers' experience, and there are still many problems in domestic forklifts compared with foreign countries. In this paper, the forklift gantry is taken as the research object, and four typical surrogate modeling techniques, namely PRS, KRG, RBF, and SVR models, are used for optimal design and analysis. The study shows that the KRG model has the best performance and RBF model has the worst… More >

Zhiyuan Dai, Tian Li^*, Weihua Zhang, Jiye Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1461-1489, 2023, DOI:10.32604/cmes.2023.028677 - 26 June 2023

Abstract The aerodynamic optimization design of high-speed trains (HSTs) is crucial for energy conservation, environmental preservation, operational safety, and speeding up. This study aims to review the current state and progress of the aerodynamic multi-objective optimization of HSTs. First, the study explores the impact of train nose shape parameters on aerodynamic performance. The parameterization methods involved in the aerodynamic multiobjective optimization of HSTs are summarized and classified as shape-based and disturbance-based parameterization methods. Meanwhile, the advantages and limitations of each parameterization method, as well as the applicable scope, are briefly discussed. In addition, the NSGA-II algorithm,… More >

Tran-Hieu Nguyen^*, Anh-Tuan Vu

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 429-458, 2023, DOI:10.32604/cmes.2022.020819 - 24 August 2022

Abstract Design constraints verification is the most computationally expensive task in evolutionary structural optimization due to a large number of structural analyses that must be conducted. Building a surrogate model to approximate the behavior of structures instead of the exact structural analyses is a possible solution to tackle this problem. However, most existing surrogate models have been designed based on regression techniques. This paper proposes a novel method, called CaDE, which adopts a machine learning classification technique for enhancing the performance of the Differential Evolution (DE) optimization. The proposed method is separated into two stages. During… More >

Nazia Afrin^a,*, Jonathan Lopez, Juan Ocampo

Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-7, 2022, DOI:10.5098/hmt.18.46

Abstract Large number of numerical computer simulations in engineering places is a serious burden on associated optimization problems nowadays. Kriging Surrogate based optimization (KSBO) becomes standard practice in analyzing expensive and time-consuming simulation. This paper aims to investigate the surrogate based analyze and optimization of thermal damage in living biological tissue by laser irradiation using a generalized duel phase model. The relationships of maximum temperature and thermal damage in living biological tissues of the response with two variables at a time are studied. The result shows that the surrogate model predicted response variables i.e, temperature and More >